SAP debuts Business Data Cloud with Databricks

This landmark partnership between SAP and Databricks marks a new era in enterprise data management as two leaders in their domains come together to redefine how applications and data platforms work together. The new solution natively embeds Databricks technology for data engineering, machine learning and AI workloads.

“SAP Business Data Cloud unleashes the full value of enterprise data for Business AI,” said SAP CEO Christian Klein. “It combines SAP’s unique expertise in mission-critical, end-to-end processes and semantically rich data with Databricks’ world-class data engineering capabilities to create a ground-breaking solution that helps organizations do more with their data than ever before.”

“Every company on the planet wants to get more value out of their data and greater returns on their AI investments,” said Ali Ghodsi, Co-founder and CEO of Databricks. “By joining forces with SAP, we’re helping organizations bring together all their data — regardless of format or where it lives — to govern, analyze and build domain-specific AI applications on the Databricks Data Intelligence Platform.”

Introducing the data product economy

SAP Business Data Cloud also helps SAP foster the growth of a data product economy. It delivers fully-managed SAP data products across all business processes – from finance, spend and supply chain data in SAP S/4HANA and SAP Ariba, to learning and talent data in SAP SuccessFactors. These data products maintain their original business context and semantics, providing immediate access to high-quality data without costly extraction processes. For example, if a CFO wants to assess the impact of rising inflation on profitability, SAP Business Data Cloud integrates real-time external data such as the consumer price index with financial data products such as general ledger accounts or cost centers to create a comprehensive financial snapshot.

SAP Business Data Cloud will also offer new capabilities called insight apps that use data products and AI models connected to real-time data to deliver advanced analytics and planning across all lines of business, including core enterprise analytics, finance and human resources.

“SAP Business Data Cloud will help us unlock the value of our data and drive innovation across our business,” said Markus Hartmann, Corporate Vice President and Head of Business Technology and regions Europe, APAC and IMEA, at Henkel, a multinational chemical and consumer goods company. “Its semantically rich data products and deep Databricks integration will enhance our existing data products and empower us to model scenarios and leverage AI insights, building a sustainable future for our data ecosystems.”

Delivering on the full promise of AI agents

SAP Business Data Cloud will improve how Joule, SAP’s generative AI copilot, accelerates cross-functional workflows and improves business decision-making with AI agents. Powered by the highest-quality enterprise dataset in the industry – and the SAP Knowledge Graph solution, which provides a business-friendly model of data – Joule agents deeply understand end-to-end processes and can collaborate across functions to solve complex business challenges, something no other agent builder technology can do out of the box.

Underscoring today’s announcement and its significance for AI innovation, SAP also unveiled a series of ready-to-use Joule agents across finance, service, sales and more to come across the SAP Business Suite. In finance, for example, agents will work together across a variety of tasks to process claims faster and improve cashflow. Joule sales agents, meanwhile, will accelerate multi-step business processes to resolve disputes and process customer inquiries faster.

SAP today also announced a powerful new agent builder capability, so customers can build and deploy their own AI agents alongside SAP's library of ready-to-deploy Joule agents. SAP's decades of business process expertise are built into the guided workflow so users can ground their custom agents in the most relevant data and business context.